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. Author manuscript; available in PMC: 2024 Jul 1.
Published in final edited form as: IEEE Trans Pattern Anal Mach Intell. 2023 Jun 5;45(7):9149–9168. doi: 10.1109/TPAMI.2023.3237667

TABLE 7.

Execution time of the K-means solutions and other competitive methods in seconds.

Task Data set Competitive methods K-means solution
CSPA HCC PTGP KCC
Consensus clusteringwith utility function iris 1.34 4.57 285 0.29
cranmed 5.27 105.41 35.76 0.44
hitech 4.77 102.93 36.93 0.43
k1b 5.66 119.36 35.27 0.21
mm 6.57 112.34 10.61 0.14
CSPA HCC PTGP SEC
Consensus clusteringwith co-association matrix cacmcisi 18.55 543.20 117.69 0.25
classic 32.14 1640.71 524.76 0.62
la12 21.48 1148.17 44.27 0.17
reviews 10.97 397.16 26.89 0.12
wine 0.83 4.57 2.85 0.05
CNMF LCVQE KCC PLCC
Constrained clustering breast 0.43 0.05 0.27 0.01
ecoli 0.19 0.03 0.22 0.01
iris 0.13 0.01 0.07 0.01
pendigits 195.38 76.73 4.98 0.45
satimage 0.05 0.01 0.10 0.01
LOF FABOD iForest BP COR
Outlier detection caltech 13.69 140.68 6.91 12.86 0.14
fbis 17.54 1319.21 12.60 15.66 0.38
re1 16.86 738.22 8.50 20.03 0.10
wap 26.81 1811.28 8.53 36.58 0.19
yeast 0.09 3.44 4.35 0.28 0.03

Note: All the algorithms in the above table were implemented by MATLAB and run on a Ubuntu 14.04 platform with Intel Core i7-6900K @ 3.2GHz and 64 GB RAM.